Triple
T30890935
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | No. 2 OCU |
E786894
|
entity |
| Predicate | aircraftRoleTrained |
P174093
|
FINISHED |
| Object | fighter |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: fighter | Statement: [No. 2 OCU, aircraftRoleTrained, fighter]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: aircraftRoleTrained Context triple: [No. 2 OCU, aircraftRoleTrained, fighter]
-
A.
aircraftTrainedOn
Indicates that an aircraft has been used as the platform or subject for training a person or crew in its operation or related skills.
-
B.
hasFixedWingTrainingRole
Indicates that an entity serves in a training capacity specifically related to the operation or use of fixed-wing aircraft.
-
C.
aircraftRoleRequired
Indicates that a specific operational role or function is required of an aircraft within a given context or mission.
-
D.
aircraftRoleOperated
Indicates that an entity operates or has operated in a specified role or function within the context of aircraft operations.
-
E.
hasRoleInAviation
Indicates that an entity holds or has held a specific role, position, or function within the field of aviation.
- F. None of above. chosen
Provenance (4 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f224bbfa7c81908448e0c261c523e3 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f6bcc425588190afd0dceba43ed79f |
completed | May 3, 2026, 3:11 a.m. |
| PD | Predicate disambiguation | batch_69f6ba6cef208190bc5cd43d96127004 |
completed | May 3, 2026, 3:01 a.m. |
| PDg | Predicate description generation | batch_69f6bbbe23d48190b2aa662d69b41900 |
completed | May 3, 2026, 3:06 a.m. |
Created at: April 29, 2026, 8:49 p.m.